Reception device and reception method

ABSTRACT

A reception unit for receiving a signal representing a bit sequence, a channel estimation unit for estimating channel variation that the received signal undergoes and calculating a channel estimation value representing the channel variation, and a demodulation unit for demodulating the signal by using the channel estimation value and restoring each bit included in the bit sequence represented by the received signal are included, and the demodulation unit performs demodulation of the received signal by using a value indicating magnitude of error included in the channel estimation value.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a reception device and a receptionmethod.

This application claims priority based on Japanese Patent ApplicationNo. 2013-042405 filed in Japan on Mar. 4, 2013, the content of which isincorporated herein.

2. Description of Related Art

In radio communication, a data signal transmitted from a transmitantenna is reflected and diffracted by a scattering body around thetransmit antenna or a receive antenna, and is received by the receiveantenna. The signal to be received is influenced in such a manner thatradio waves strengthen and attenuate each other by a lot of scatteringbodies, which is called fading. A receiver (also referred to as areception device) needs to compensate for the influence on the datasignal caused by fading. In a cellular communication system of third andfollowing generations, such as W-CDMA (Wideband Code Division MultipleAccess) or LTE (Long Term Evolution), a pilot signal (a pilot symbol, areference signal), which is a signal known between a transmitter andreceiver, is inserted periodically in a data signal. The receiver (orthe reception device) is able to estimate the influence of fading(called propagation channel variation, or simply a propagation channelor a channel in some cases) by using the pilot signal, and by using theestimated channel, compensate for the influence of the fading on thereceived data signal. The channel estimation makes it possible totransfer data without errors.

For transferring data without errors, error correction coding isgenerally used in radio communication. With the error correction coding,it is possible to correct error caused in a channel by performing codingwith redundancy for a data bit sequence for transmission and performingdecoding by using the redundancy with the receiver. In this case, aturbo code, an LDPC code or the like is used for the error correctioncoding, and a bit LLR (Log Likelihood Ratio) is generally input to sucha decoder.

Meanwhile, for example, in OFDM (Orthogonal Frequency DivisionMultiplexing), when a transmission data signal in a k-th subcarrier isX_(d)(k), a complex channel gain of a channel is H(k), and noisereceived by the receiver is n_(d)(k), a received signal in the k-thsubcarrier Y_(d)(k) at the time of data reception is represented by afollowing formula 1.

[Expression 1]

Y _(d)(k)=H(k)X _(d)(k)+N _(d)(k)  (formula 1)

In the OFDM, since subcarriers are independent from each other, each ofthem is able to be regarded as a narrow-band single carrier. In order tosimplify this description, each formula is represented with lowercaseletters and an index of k is omitted to thereby obtain a followingformula 2.

[Expression 2]

y _(d) =hx _(d) +n _(d)  (formula 2)

When x_(d) is BPSK (Binary Phase Shift keying) and x_(d)={+√E_(s),−√E_(s)} is provided (where E_(s) is a spectral density of atransmission signal), a bit LLR λ_(e) is represented by a followingformula 3 according to NPL 1.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 3} \right\rbrack & \; \\{\lambda_{e} = {\ln \frac{p\left( {{y_{d}x_{d}} = {+ \sqrt{E_{s}}}} \right)}{p\left( {{y_{d}x_{d}} = {- \sqrt{E_{s}}}} \right)}}} & \left( {{formula}\mspace{14mu} 3} \right)\end{matrix}$

p(y_(d)|x_(d)=+√E_(s)) represents a probability for a received signal tobe y_(d) when the transmission signal x_(d) is +√E_(s). When the noisen_(d) conforms to a complex Gaussian process with an average of 0 and anoise power spectral density of N₀, p(y_(d)|x_(d)=+√E_(s)) isrepresented by a following formula 4.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 4} \right\rbrack & \; \\{{p\left( {{y_{d}x_{d}} = {+ \sqrt{E_{s}}}} \right)} = {\frac{1}{\pi \; N_{0}}{\exp\left( {- \frac{{{y_{d} - {h \cdot \left( {+ \sqrt{E_{s}}} \right)}}}^{2}}{N_{0}}} \right)}}} & \left( {{formula}\mspace{14mu} 4} \right)\end{matrix}$

The formula 3 is able to be modified like a following formula 5 bysimilarly obtaining such a formula in the case of x_(d)=−√E_(s).

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 5} \right\rbrack & \; \\\begin{matrix}{\lambda_{e} = {\ln \frac{\frac{1}{\pi \; N_{0}}{\exp\left( {- \frac{{{y_{d} - {\sqrt{E_{s}}h}}}^{2}}{N_{0}}} \right)}}{\frac{1}{\pi \; N_{0}}{\exp\left( {- \frac{{{y_{d} + {\sqrt{E_{s}}h}}}^{2}}{N_{0}}} \right)}}}} \\{= {\frac{4\sqrt{E_{s}}}{N_{0}}{{Re}\left\lbrack {h^{*}y_{d}} \right\rbrack}}}\end{matrix} & \left( {{formula}\mspace{14mu} 5} \right)\end{matrix}$

In this manner, when the transmission signal is the BPSK, the bit LLR isable to be calculated based on a result that the received signal y_(d)is multiplied by a complex conjugate h* of a channel h. Further, errorcorrection decoding is able to be performed by inputting the obtainedbit LLR to a decoder.

Though the formula 5 needs information concerning a complex channel gainh, a channel applied to data actually is unknown. Thus, NPL 2 describesthat a reception device estimates a channel gain by using a pilot signalwhich is transmitted with data by a transmission device and uses theestimated value instead of the channel gain applied to the dataactually.

CITATION LIST Non Patent Literatures

NPL 1: L. Hanzo, T. H. Liew, B. L. Yeap, Turbo Coding, TurboEqualisation and Space-Time coding for Transmission over FadingChannels, IEEE Press-John Wiley.

NPL 2: S. Ferrara, M. Nicoli, U. Spagnolini, “Soft-iterative estimationof structured channels: performance analysis and comparison,” Intern.Workshop on Convergent Tech. (IWCT). 05, Oulu, Finland, 6-10 Jun. 2005

Here, the formula 5 is likelihood when a channel gain is ideallyestimated without regarding errors, that is, when a probability modelfor signal detection is able to be represented by using data with noisehaving an ideal Gaussian distribution. On the other hand, when a channelestimation value is used, noise is added also to the channel estimationvalue as well as to a data signal. Therefore, noise included in a datasignal that is obtained as a result of channel compensation of the datasignal by using the channel estimation value does not always have anideal Gaussian distribution. Accordingly, there is a problem that thebit LLR calculated by using the formula 5 includes error caused by datawith noise that does not conform to a Gaussian distribution.

The invention has been made in view of such circumstances and provides areception device and a reception method capable of suppressing errorincluded in a bit LLR obtained by demodulation using a channelestimation value.

SUMMARY OF THE INVENTION

(1) The invention has been made in order to solve the aforementionedproblem, and one aspect of the invention is a reception deviceincluding: a reception unit for receiving a signal representing a bitsequence; a channel estimation unit for estimating channel variationthat the signal undergoes and calculating a channel estimation valuerepresenting the channel variation; and a demodulation unit fordemodulating the signal by using the channel estimation value andrestoring each bit included in the bit sequence, in which thedemodulation unit performs demodulation of the signal by using a valueindicating magnitude of error (MSE: Mean Square Error) included in thechannel estimation value.

(2) Another aspect of the invention is the reception device according to(1), in which the demodulation unit may perform the demodulation byusing a probability density function that is a probability densityfunction of the signal and that is a product of two probability densityfunctions each represents a corresponding independent Gaussian variableby using at least the signal and the value indicating the magnitude ofthe error.

(3) Another aspect of the invention is the reception device according to(1) or (2), which may include a decoding unit for performing errorcorrection decoding for the bit restored by the demodulation unit byusing a state transition probability according to reception power of thesignal.

(4) Another aspect of the invention is the reception device according toany one of (1) to (3), which may include a decoding unit for performingerror correction decoding for the bit restored by the demodulation unit;and a replica generation unit for generating a replica of a transmissionsymbol by using the bit subjected to the error correction decoding, andin which channel estimation by the channel estimation unit, demodulationby the demodulation unit, error correction decoding by the decoding unitand generation of the replica by the replica generation unit may beperformed iteratively, and the channel estimation unit may performchannel estimation by using the replica generated by the replicageneration in second and subsequent times of the iteration.

(5) Another aspect of the invention is the reception device according toany one of (1) to (4), in which the channel estimation unit calculates,for each reception symbol included in the received signal, a channelestimation value used for demodulating the reception symbol, and achannel estimation value used for demodulating a first reception symbolis a value obtained by performing channel estimation without using areplica of a transmission symbol of the first reception symbol.

(6) Another aspect of the invention is a reception method, including: afirst step of receiving a signal representing a bit sequence; a secondstep of estimating channel variation that the signal undergoes andcalculating a channel estimation value representing the channelvariation; and a third step of demodulating the signal by using thechannel estimation value and restoring each bit included in the bitsequence, in which demodulation of the signal is performed by using avalue indicating magnitude of error included in the channel estimationvalue at the third step.

According to one aspect of the invention, it is possible to suppresserror included in a bit LLR obtained by demodulation using a channelestimation value.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic block diagram showing an example of aconfiguration of a communication system in a first embodiment of theinvention.

FIG. 2 is a schematic block diagram showing an example of aconfiguration of a transmitter of a base station device 101 in theembodiment.

FIG. 3 is a view showing an example of a frame composition of signalstransmitted by the base station device 101 in the embodiment.

FIG. 4 is a schematic block diagram showing an example of aconfiguration of a receiver of a terminal device 102 in the embodiment.

FIG. 5 is a schematic block diagram showing a configuration of ademodulation unit 407 (here, β=1) in the embodiment.

FIG. 6 is a view showing results of simulation of the embodiment.

FIG. 7 is a view showing results of simulation of a modified example 1of the embodiment.

FIG. 8 is a schematic block diagram showing an example of aconfiguration of a receiver of a terminal device 102 a in a secondembodiment of the invention.

DETAILED DESCRIPTION OF THE INVENTION First Embodiment

A first embodiment of the invention will hereinafter be described withreference to drawings. FIG. 1 is a schematic block diagram showing anexample of a configuration of a communication system in the presentembodiment. A communication system 10 in the present embodiment isconstituted by including a base station device 101 and a terminal device102. The communication system 10 is a system in which the base stationdevice 101 transmits data to the terminal device 102. Though oneterminal device 102 is illustrated in FIG. 1, two or more terminaldevices 102 may exist. Moreover, the present embodiment and embodimentsbelow are intended for downlink (transmission from the base stationdevice 101 to the terminal device 102), but are also applicable touplink (data transmission from the terminal device to the base stationdevice).

Further, though OFDM (Orthogonal Frequency Division Multiplexing) isassumed as a communication method, applying to any communicationmethods, such as narrow-band single carrier transmission, SC-FDMA(Single Carrier Frequency Division Multiple Access, also referred to asDFT-S-OFDM (Discrete Fourier Transform Spread OFDM)), DS-CDMA (DirectSequence Code Division Multiple Access) or MC-CDMA (Multi-Carrier CDMA),is possible regardless of cable communication or radio communication. Inthe case of applying, processing disclosed in the present embodiment maybe applied for each subcarrier or for each symbol after equalization.Moreover, data to be transmitted may be not only an information bitsequence but control information.

FIG. 2 is a schematic block diagram showing an example of aconfiguration of a transmitter of the base station device 101 in thepresent embodiment. The base station device 101 is constituted byincluding a coding unit 201, an interleave unit 202, a modulation unit203, a reference signal generation unit 204, a frame composition unit205, an IFFT (Inverse Fast Fourier Transform) unit 206, a CP (CyclicPrefix) insertion unit 207, a radio transmission unit 208, and atransmit antenna 209. Note that, in addition to each of the units, thebase station device 101 is constituted by including a configuration thata base station device generally has, such as a reception unit thatreceives a radio signal from the terminal device 102, but illustrationand description thereof will be omitted here.

Moreover, the base station device 101 includes one transmit antenna inFIG. 2, but may have two or more and use a publicly known MIMO techniquesuch as spatial multiplex or transmit antenna diversity. Note that, thenumber of transmit antennas may be considered as the number of antennaports, and since the number of antenna ports is defined as the number oftransmit antennas capable of transmitting different transmissionsignals, when a same signal is transmitted by, for example, threetransmit antennas, the number of antenna ports is defined as one.

The coding unit 201 applies error correction coding such as turbo codeor convolutional code to an information bit sequence B which is input. Acoded bit sequence which is coded by the coding unit 201 is input to theinterleave unit 202. The interleave unit 202 performs processing ofsorting the coded bit sequence, which is input, in a predetermined orderstored in the interleave unit 202. Coded bits sorted by the interleaveunit 202 are input to the modulation unit 203. The modulation unit 203converts the coded bit sequence which is input from the interleave unit202 into a modulation symbol by BPSK (Binary Phase Shift Keying). Theobtained modulation symbol is input to the frame composition unit 205.

The reference signal generation unit 204 generates a reference signal,which is a known signal in the terminal device 102, to input to theframe composition unit 205. The frame composition unit 205 composes atransmission frame by using the reference signal input from thereference signal generation unit 204 and the modulation symbol inputfrom the modulation unit 203. FIG. 3 is a view showing an example of aframe composition of signals transmitted by the base station device 101.The frame composition is essentially a frame composition used for uplinkof LTE (Long Term Evolution), but is used to simplify description. FIG.3 represents a subframe when one RB (Resource Block) is used, and one RBis formed by one hundred and sixty-eight REs (Resource Elements) intotal of twelve subcarriers and fourteen OFDM symbols.

Though description will be given below for a case where one frame iscomposed of two slots and channel estimation is performed in each of theslots, the invention is not limited thereto and may perform channelestimation for each frame and is applicable also to a frame compositionother than that of FIG. 3. Here, the resource element is a minimum unitof a resource capable of being used in a frequency direction and a timedirection.

The frame composition unit 205 arranges the reference signal input fromthe reference signal generation unit 204 in a black resource element ofFIG. 3 and arranges the data signal input from the modulation unit 203in a white resource element to compose a transmission frame. Though onlyone RB is shown in FIG. 3, the number of RBs is not limited to one andmay be plural.

With reference back to FIG. 2, the transmission frame composed by theframe composition unit 205 is input to the IFFT unit 206 for each of oneOFDM symbol. The IFFT unit 206 applies IFFT of N_(FFT) points to each ofOFDM symbols input from the frame composition unit 205 to therebyperform transformation from a frequency domain signal into a time domainsignal. At this time, zero is input to a subcarrier in which neither thereference signal nor the data signal is arranged. The signal transformedfrom the frequency domain signal into the time domain signal by the IFFTat the IFFT unit 206 is input to the CP insertion unit 207. By copyingbackward N_(CP) points of the time domain signal of N_(FFT) points toinsert to a head, the CP insertion unit 207 generates the time domainsignal of (N_(FFT)+N_(CP)) points. The CP insertion unit 207 inputs thegenerated time domain signal to the radio transmission unit 210. Theradio transmission unit 208 applies D/A (Digital-to-Analog) conversion,band restriction filtering, up-conversion and the like to the inputsignal. An output of the radio transmission unit 208 is transmitted tothe terminal device 102 through the transmit antenna 209.

FIG. 4 is a schematic block diagram showing an example of aconfiguration of a receiver of the terminal device 102 in the presentembodiment. The terminal device 102 is constituted by including areceive antenna 401, a radio reception unit 402, a CP removal unit 403,an FFT (Fast Fourier Transform) unit 404, a data signal extraction unit405, a channel estimation unit 406, a demodulation unit 407, ade-interleave unit 408, and a decoding unit 409. Note that, in additionto each of the units, the terminal device 102 is constituted byincluding a configuration that a terminal device performing radiocommunication with a base station device generally has, such as atransmission unit that transmits a radio signal to the base stationdevice 101, but illustration and description thereof will be omittedhere.

The receive antenna 401 receives a signal transmitted from the basestation device 101. The terminal device 102 has one receive antenna inthe present embodiment, but may have a plurality of receive antennas anda publicly known technique such as spatial filtering or receive antennadiversity may be applied.

The signal received by the receive antenna 401 is input to the radioreception unit 402. The radio reception unit 402 applies processing,such as down-conversion, band restriction filtering and A/D(Analog-to-Digital) conversion, to the input signal.

A processing result by the radio reception unit 402 is input to the CPremoval unit 403. The CP removal unit 403 partitions the received signalfor each of (N_(FFT)+N_(CP)) points, and removes N_(CP) points from ahead of the received signal of (N_(FFT)+N_(CP)) points. A signal foreach of N_(FFT) points, which is a result of removal by the CP removalunit 403, is input to the FFT unit 404. The FFT unit 404 applies FFT(Fast Fourier Transform) of N_(FFT) points to the time domain signal foreach of N_(FFT) points, which is input, to thereby performtransformation from the time domain signal into a frequency domainsignal (received frequency domain signal).

Note that, the processing performed at the FFT unit 404 may not benecessarily FFT, and may be, for example, DFT (Discrete FourierTransform). The received frequency domain signal which is a result ofthe transformation by the FFT unit 404 is input to the data signalextraction unit 405. The data signal extraction unit 405 demultiplexes areference signal (received reference signal) from the received frequencydomain signal to input to the channel estimation unit 406. The datasignal extraction unit 405 further demultiplexes a data signal or acontrol signal from the received frequency domain signal to input to thedemodulation unit 407. The data signal or the control signal, which isdemultiplexed, is referred to as a received data signal below.

The channel estimation unit 406 uses the received reference signal,which is input, to perform estimation of channel variation (hereinafter,referred to as channel estimation) and estimation of average noise power(or a noise power spectral density, noise energy) for compensating forinfluence of fading (channel variation) applied to the data signal on achannel. Though a channel estimation method applied in the channelestimation unit 406 may be any one, description will be given in thepresent embodiment by exemplifying a case where channel estimation withan LS (Least Square) reference is used as the channel estimation method.When a received reference signal y_(p) in a certain subcarrier isrepresented by a formula 6 by using a transmitted reference signalx_(p), a channel h, and noise n_(p) when the reference signal isreceived, a channel estimation value h (hat) with the LS reference isrepresented by a formula 7.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 6} \right\rbrack & \; \\{y_{p} = {{hx}_{p} + n_{p}}} & \left( {{formula}\mspace{14mu} 6} \right) \\\left\lbrack {{Expression}\mspace{14mu} 7} \right\rbrack & \; \\{\hat{h} = {\frac{y_{p}}{x_{p}} = {h + {x_{p}^{- 1}n_{p}}}}} & \left( {{formula}\mspace{14mu} 7} \right)\end{matrix}$

The channel estimation unit 406 is premised to apply channel estimationbased on the formula 7 to a resource element in which the referencesignal has been received (black part in FIG. 3) and perform zero-orderinterpolation, but may calculate a channel estimation value in aresource element in which data has been received (white part in FIG. 3)by interpolation such as first-order interpolation or MMSE (Minimum MeanSquare Error) interpolation. The obtained channel estimation value isinput to the demodulation unit 407. Further, in addition to the channelestimation value h (hat), an average noise power spectral density N₀ anda transmission power spectral density of a data signal E_(S) are inputto the demodulation unit 407. For simplifying description, it is setthat the transmission power spectral density of the data signal E_(S)and a transmission power spectral density of a pilot signal E_(P) areknown in a receiver. However, a formula E_(S) (or E_(P)) which isfinally used for computation is able to be developed to a formula bywhich multiplication by a square of a channel gain h (or channelestimation value h (hat)). A result of multiplying by the square of thechannel gain h is the received power spectral density and is able to beobserved also in the receiver, so that the present embodiment isapplicable without difficulty even when a transmission power spectrum isnot known. In this case, development of a formula is to be performeddifferently from those of the present embodiment and other embodiments,but a bit LLR is able to be calculated based on similar concept.

The demodulation unit 407 demodulates the received data signal, which isinput from the data signal extraction unit 405, by using thecorresponding channel estimation value input from the channel estimationunit 406. With the demodulation, the demodulation unit 407 restorescoded bits represented by the received data signal to calculate the LLRof each of the bits. Note that, channel compensation for the receiveddata signal and restoration of the bits represented by the received datasignal are performed with the demodulation by the demodulation unit 407.When performing the demodulation, the demodulation unit 407 in thepresent embodiment suppresses error included in a bit sequence by usingvariance of the channel estimation value. Processing of the demodulationunit 407 will be described in detail below.

A bit sequence output by the demodulation unit 407 is input to thede-interleave unit 408. The de-interleave unit 408 applies processing ofde-interleaving the interleave having been applied in the base stationdevice 101 (de-interleaving processing) to the input bit sequence. Thebit sequence subjected to the de-interleaving processing by thede-interleave unit 408 is input to the decoding unit 409.

The decoding unit 409 performs decoding for the bit sequence subjectedto the de-interleaving processing based on error correction codingapplied in the base station device 101, and outputs an obtained restoredbit sequence T.

When performing the decoding, the decoding unit 409 uses aninstantaneous received power spectral density |h|²E_(S) and the averagenoise power spectral density N₀, which are obtained from the channelestimation unit 406, and description thereof will be given in detailbelow.

Next, the processing of the demodulation unit 407 will be described indetail. When an ideal value is obtained by channel estimation by thechannel estimation unit 406 without influence of noise or the like, thedemodulation unit 407 may merely calculate the LLR based on the formula5. However, since the channel estimation value h (hat) is calculated bythe formula 7, an observable value z obtained by replacing the channel hin the formula 5 with a channel estimation value h (hat) is not matchedwith λ_(e) and has a value including error ε as shown in a formula 8.Here, in a right side of a first row of the formula 8, E_(s) is known,N₀ is calculated at the time of channel estimation, h (hat) is obtainedby channel estimation, and y_(d) is a received signal. That is, theobservable value z is a value which is able to be calculated by valuesthereof.

In the present embodiment, the demodulation unit 407 calculates a loglikelihood ratio of the observable value z and inputs a sequence of thelog likelihood ratio to the de-interleave unit 408 as a bit sequence.Note that, it is considered that error of estimation is included also inthe average noise power spectral density N₀ in the formula 8, and it isset that the error is included in a channel estimation value.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 8} \right\rbrack & \; \\\begin{matrix}{z = {\frac{4\sqrt{E_{s}}}{N_{0}}{{Re}\left\lbrack {{\hat{h}}^{*}y_{d}} \right\rbrack}}} \\{= {\lambda_{e} + ɛ}}\end{matrix} & \left( {{formula}\mspace{14mu} 8} \right)\end{matrix}$

For deriving a formula for calculating the log likelihood ratio of theobservable value z, first, the formula 8 is modified like a followingformula 9. In the formula 9, a and b are represented by a formula 10.Further, when γ and β in the formula 10 are set as a formula 11, a and bin the formula 9 serve as independent Gaussian variables.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 9} \right\rbrack & \; \\{z = {{\frac{4\sqrt{E_{s}}}{N_{0}}{{Re}\left\lbrack {{\hat{h}}^{*}y_{d}} \right\rbrack}} = {\sqrt{\beta}\left( {{a}^{2} - {b}^{2}} \right)}}} & \left( {{formula}\mspace{14mu} 9} \right) \\\left\lbrack {{Expression}\mspace{14mu} 10} \right\rbrack & \; \\\left\{ \begin{matrix}{a = {\sqrt{\gamma}\left( {h + \frac{y_{d}}{\sqrt{E_{s}\beta}}} \right)}} \\{b = {\sqrt{\gamma}\left( {h - \frac{y_{d}}{\sqrt{E_{s}\beta}}} \right)}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 10} \right) \\\left\lbrack {{Expression}\mspace{14mu} 11} \right\rbrack & \; \\\left\{ \begin{matrix}{\gamma = \frac{E_{s}}{N_{0}}} \\{\beta = {\frac{1}{\sigma_{est}^{2}}\frac{N_{0}}{E_{s}}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 11} \right)\end{matrix}$

In a formula 11, σ_(est) ² is mean square error (MSE) of the actualchannel h and the channel estimation value h (hat). That is, σ_(est) ²is a value indicating a magnitude of the error of the channel estimationvalue h (hat). σ_(est) ² depends on the channel estimation method, but,for example, in the case of LS channel estimation, is represented by aformula 12. Therefore, when the channel estimation method is the LSchannel estimation, β is shown in a following formula 13. Note that,E_(p) is an average transmission power spectral density of a pilotsignal.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 12} \right\rbrack & \; \\{\sigma_{est}^{2} = \frac{N_{0}}{E_{p}}} & \left( {{formula}\mspace{14mu} 12} \right) \\\left\lbrack {{Expression}\mspace{14mu} 13} \right\rbrack & \; \\{\beta = \frac{E_{p}}{E_{s}}} & \left( {{formula}\mspace{14mu} 13} \right)\end{matrix}$

Further, since a and b are independent Gaussian variables, z isdetermined uniquely by absolute values of a and b, and thus a relationof a following formula 14 is satisfied.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 14} \right\rbrack & \; \\\begin{matrix}{{p\left( {zx_{d}} \right)} = {p\left( {{a},{{b}x_{d}}} \right)}} \\{= {{p\left( {{a}x_{d}} \right)}{p\left( {{b}x_{d}} \right)}}}\end{matrix} & \left( {{formula}\mspace{14mu} 14} \right)\end{matrix}$

Next, the LLR of z (λ_(Z)) is represented by a following formula 15 byusing the formula 14.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 15} \right\rbrack & \; \\\begin{matrix}{\lambda_{z} = {\ln \frac{p\left( {{zx_{d}} = {+ \sqrt{E_{s}}}} \right)}{p\left( {{zx_{d}} = {- \sqrt{E_{s}}}} \right)}}} \\{= {\ln \frac{\left( {{{p{a}}x_{d}} = {+ \sqrt{E_{s}}}} \right){p\left( {{{b}x_{d}} = {+ \sqrt{E_{s}}}} \right)}}{\left( {{{p{a}}x_{d}} = {- \sqrt{E_{s}}}} \right){p\left( {{{b}x_{d}} = {- \sqrt{E_{s}}}} \right)}}}}\end{matrix} & \left( {{formula}\mspace{14mu} 15} \right)\end{matrix}$

Here, an average value μ_(a) and variance N_(a) of a of the formula 10,and an average value μ_(b) and variance N_(b) of b are provided by aformula 16 and a formula 17, respectively.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 16} \right\rbrack & \; \\\left\{ \begin{matrix}{{\mu_{a}\left( x_{d} \right)} = {{E\lbrack a\rbrack} = {\sqrt{\gamma}\left( {1 + \frac{x_{d}}{\sqrt{E_{s}\beta}}} \right)h}}} \\{N_{a} = {{V\lbrack a\rbrack} = \frac{2}{\beta}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 16} \right) \\\left\lbrack {{Expression}\mspace{14mu} 17} \right\rbrack & \; \\\left\{ \begin{matrix}{{\mu_{b}\left( x_{d} \right)} = {{E\lbrack b\rbrack} = {\sqrt{\gamma}\left( {1 - \frac{x_{d}}{\sqrt{E_{s}\beta}}} \right)h}}} \\{N_{b} = {{V\lbrack b\rbrack} = \frac{2}{\beta}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 17} \right)\end{matrix}$

Here, a and b have the same variance, N_(a)=N_(b)=N_(ab) is set. Withthe aforementioned average and variance, p(a|x_(d)) is provided by afollowing formula 18.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 18} \right\rbrack & \; \\\begin{matrix}{{p\left( {ax_{d}} \right)} = {\frac{1}{\pi \; N_{ab}}{\exp\left( {- \frac{{{a - {\mu_{a}\left( x_{d} \right)}}}^{2}}{N_{ab}}} \right)}}} \\{= {p\left( {{a},{\theta_{a}x_{d}}} \right)}}\end{matrix} & \left( {{formula}\mspace{14mu} 18} \right) \\\left\lbrack {{Expression}\mspace{14mu} 19} \right\rbrack & \; \\\left\{ \begin{matrix}{a = {{a}\left( {{\cos \; \theta_{a}} + {j\; \sin \; \theta_{a}}} \right)}} \\{b = {{b}\left( {{\cos \; \theta_{b}} + {j\; \sin \; \theta_{b}}} \right)}} \\{{\mu_{a}\left( x_{d} \right)} = {{{\mu_{a}\left( x_{d} \right)}}\left( {{\cos \; \theta_{\mu_{a}{(x_{d})}}} = {jsin\theta}_{\mu_{a}{(x_{d})}}} \right)}} \\{{\mu_{b}\left( x_{d} \right)} = {{{\mu_{b}\left( x_{d} \right)}}\left( {{\cos \; \theta_{\mu_{b}{(x_{d})}}} = {jsin\theta}_{\mu_{b}{(x_{d})}}} \right)}} \\{\theta_{a} = {\tan^{- 1}\frac{{Im}\lbrack a\rbrack}{{Re}\lbrack a\rbrack}}} \\{\theta_{b} = {\tan^{- 1}\frac{{Im}\lbrack b\rbrack}{{Re}\lbrack b\rbrack}}} \\{\theta_{\mu_{a}{(x_{d})}} = {\tan^{- 1}\frac{{Im}\left\lbrack {\mu_{a}\left( x_{d} \right)} \right\rbrack}{{Re}\left\lbrack {\mu_{a}\left( x_{d} \right)} \right\rbrack}}} \\{\theta_{\mu_{b}{(x_{d})}} = {\tan^{- 1}\frac{{Im}\left\lbrack {\mu_{b}\left( x_{d} \right)} \right\rbrack}{{Re}\left\lbrack {\mu_{b}\left( x_{d} \right)} \right\rbrack}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 19} \right)\end{matrix}$

Since the LLR of the formula 15 is represented only by the absolutevalue of a, by performing peripheral integration with respect to a phasein the formula 18, a formula 20 is obtained. In the formula 20, I₀(x) isa modified Bessel function of the first kind and zero order and isrepresented by a following formula.

$\begin{matrix}{\mspace{79mu} \left\lbrack {{Expression}\mspace{14mu} 20} \right\rbrack} & \; \\\begin{matrix}{{p\left( {{a}x_{d}} \right)} = {\int_{- \pi}^{\pi}{{p\left( {{a},{\theta_{a}x_{d}}} \right)}\ {\theta_{a}}}}} \\{= {\frac{2{a}}{\pi \; N_{ab}}{\exp \left( {- \frac{{a}^{2} + {{\mu_{a}\left( x_{d} \right)}}^{2}}{N_{ab}}} \right)}{\int_{- \pi}^{\pi}{\left( \frac{{a}{{\mu_{a}\left( x_{d} \right)}}{\cos \left( {\theta_{a} - \theta_{\mu_{a}}} \right)}}{N_{ab}} \right)\ {\theta_{a}}}}}} \\{= {\frac{2{a}}{\; N_{ab}}{\exp \left( {- \frac{{a}^{2} + {{\mu_{a}\left( x_{d} \right)}}^{2}}{N_{ab}}} \right)}{I_{0}\left( \frac{2{a}{{\mu_{a}\left( x_{d} \right)}}^{2}}{N_{ab}} \right)}}}\end{matrix} & \left( {{formula}\mspace{14mu} 20} \right) \\{\mspace{79mu} \left\lbrack {{Expression}\mspace{14mu} 21} \right\rbrack} & \; \\{\mspace{79mu} {{I_{0}(x)} = {\frac{1}{\pi}{\int_{0}^{\pi}{{\exp \left( {x\; \cos \; \theta} \right)}\ {\theta}}}}}} & \left( {{formula}\mspace{14mu} 21} \right)\end{matrix}$

By calculating b similarly, the formula 15 is able to be modified like afollowing formula 22.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 22} \right\rbrack & \; \\\begin{matrix}{\lambda_{z} = \frac{p\left( {{zx_{d}} = {+ \sqrt{E_{s}}}} \right)}{p\left( {{zx_{d}} = {- \sqrt{E_{s}}}} \right)}} \\{= {\ln \frac{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( {+ \sqrt{E_{s}}} \right)}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{b}\left( {+ \sqrt{E_{s}}} \right)}}}{N_{ab}} \right)}}{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( {- \sqrt{E_{s}}} \right)}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{b}\left( {- \sqrt{E_{s}}} \right)}}}{N_{ab}} \right)}}}}\end{matrix} & \left( {{formula}\mspace{14mu} 22} \right)\end{matrix}$

In the case of β=1, that is, when the noise power spectral densityincluded in the received data signal and MSE (mean square error) of thechannel estimation value are equal (when the data signal and thereference signal have equal average transmission power in the LS channelestimation), the formula 22 becomes a following formula 23.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 23} \right\rbrack & \; \\{\lambda_{z} = {\ln \frac{I_{0}\left( {2\sqrt{\gamma}{a}{h}} \right)}{I_{0}\left( {2\sqrt{\gamma}{b}{h}} \right)}}} & \left( {{formula}\mspace{14mu} 23} \right)\end{matrix}$

Here, an approximation formula of a following formula 24 is able to beused for the modified Bessel function of the first kind and zero orderI₀.

Alternatively, approximation of a following formula 25 is also able tobe used.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 24} \right\rbrack & \; \\{{{I_{0}(x)} = {\frac{1}{\sqrt{2\pi \; x}}{\exp (x)}}},{x\operatorname{>>}1}} & \left( {{formula}\mspace{14mu} 24} \right) \\\left\lbrack {{Expression}\mspace{14mu} 25} \right\rbrack & \; \\\begin{matrix}{\lambda_{z} = {\ln \frac{I_{0}\left( {2\sqrt{\gamma}{a}{h}} \right)}{I_{0}\left( {2\sqrt{\gamma}{b}{h}} \right)}}} \\{{\approx {{\ln {b}} - {\ln {a}} + {2{h}\sqrt{\gamma}\left( {{a} - {b}} \right)}}},\left( {{2{h}\sqrt{\gamma}}\operatorname{>>}0} \right)}\end{matrix} & \left( {{formula}\mspace{14mu} 25} \right)\end{matrix}$

The demodulation unit 407 in the present embodiment performsdemodulation processing by using the formula 22 described above. Themodified Bessel function of the first kind and zero order shown in theformula 24 may not be subjected to approximation necessarily and may becalculated actually. Though a channel value h which is unknown isincluded in the formulas used by the demodulation unit 407, such as theformulas 22, 23 and 25, the demodulation unit 407 in the presentembodiment performs computation by substituting the channel estimationvalue h (hat) into the channel value h. In all the formulas, only anabsolute value of the channel value h is used and the phase is notaffected, so that even when the channel estimation value h (hat) issubstituted as the channel value h into the formulas, error to be causedis small and significant deterioration of property does not occur.

Next, description will be given by using a drawing for processingperformed by the demodulation unit 407 in the case of β=1, that is, fora case where the formula 23 is used. Note that, in the case of β≠1, theLLR needs to be calculated not by the formula 23 but by the formula 22,so that the demodulation unit 407 has a different configuration from aconfiguration of FIG. 5, description of which will be omitted. FIG. 5 isa schematic block diagram showing an example of the configuration of thedemodulation unit 407 in the case of β=1. The demodulation unit 407 isconstituted by including an MSE setting unit 501, a first variablecalculation unit 502, an absolute value acquisition unit 503, a secondvariable calculation unit 504, an absolute value acquisition unit 505,an absolute value acquisition unit 506, and an LLR calculation unit 507.

To the demodulation unit 407, the data signal y_(d) is input from thedata signal extraction unit 405 as well as the channel estimation valueh (hat) and the average noise power spectral density N₀ are input fromthe channel estimation unit 406. Among them, the data signal y_(d) isinput to the first variable calculation unit 502 and the second variablecalculation unit 504. The channel estimation value h (hat) is input tothe first variable calculation unit 502, the second variable calculationunit 504, and the absolute value acquisition unit 506. Though not shown,the average noise power spectral density is input to the first variablecalculation unit 502, the second variable calculation unit 504 and theLLR calculation unit 507.

The first variable calculation unit 502 calculates a value of a based onthe formula 10. The second variable calculation unit 504 calculates avalue of b based on the formula 10 similarly. The values of a and b,which are calculated by the first variable calculation unit 502 and thesecond variable calculation unit 504, are respectively input to theabsolute value acquisition units 503 and 504. The absolute valueacquisition units 503 and 505 apply, to the values of a and brepresented by complex numbers, processing for acquiring absolute valuesthereof. The calculated absolute values are input to the LLR calculationunit 507.

On the other hand, the channel estimation value h (hat) output from thechannel estimation unit 406 is also input to the absolute valueacquisition unit 506. In the same manner, the absolute value acquisitionunit 506 applies processing for acquiring an absolute value also to thechannel estimation value h (hat) which is input. The absolute value ofthe channel estimation value, which is calculated here, is input to theLLR calculation unit 507.

The LLR calculation unit 507 calculates the LLR by using the absolutevalues input from the absolute value acquisition units 503, 505 and 506,the average noise power spectral density input from the channelestimation unit 406, and the formula 23, and inputs the obtained LLR tothe de-interleave unit 408. Note that, the modified Bessel function ofthe first kind and zero order is able to be calculated by usingapproximation of the formula 24, the formula 25 and the like.

Meanwhile, when the channel estimation value is obtained ideally, theLLR conforms to a Gaussian distribution and a ratio of an average valueand variance of the LLR becomes one to two. Satisfying the ratio iscalled satisfying a consistency condition. On the other hand, when anLLR calculation method of the present embodiment is used, the LLRconforms to a Gaussian distribution but does not satisfy the consistencycondition.

In a decoder such as a turbo decoder, a state transition probability isgenerally calculated by utilizing that the ratio of the average valueand the variance becomes one to two under the consistency condition,while, in the LLR calculation method of the present embodiment, theconsistency condition is not satisfied and the ratio of the average andthe variance becomes different depending on received power. Thus, thedecoding unit 409 in the present embodiment generates and holds a tableof the ratio of the average value and the variance at each instantaneousSNR (Signal to Noise power Ratio) in the decoding unit 409, and refersto the ratio of the average and the variance according to theinstantaneous received SNR calculated by the channel estimation unit 406to reflect on the state transition probability.

Note that, the ratio of the average value and the variance at each SNR,which is calculated in advance by simulation or the like, is stored.Thereby, the decoding processing is able to be performed with a moreappropriate state transition probability compared to calculation withthe ratio of the average value and the variance as one to two at alltimes. However, decoding processing which is similar to conventional onemay be performed by performing approximation to one to two at all times.

In this manner, in the present embodiment, by using the LLR calculationmethod using σ_(est) ² indicating magnitude of error included in thechannel estimation value, it is possible to suppress the error at thetime of channel estimation by calculating the LLR with the approximationwhich is to conform to a Gaussian distribution avoided even though thereare two pieces of noise at the time of calculating the LLR. Byperforming error decision and error correction decoding by using theLLR, it is possible to improve a bit error rate compared to a case wherea conventional LLR calculation method is used.

Modified Example 1

Though description has been given in the aforementioned embodiment for acase where the BPSK is used as a modulation method, a case where QPSK isused will be described below as a modified example. That is, descriptionwill be given for processing performed by the demodulation unit 407 ofthe terminal device 102 when the modulation unit 203 of the base stationdevice 101 converts a coded bit sequence into a modulation symbol byQPSK.

When the modulation method is the QPSK, two bits forming a QPSK symbolare set as c₀ and c₁, respectively. In this case, χ_(d)ε{χ₀, χ₁, χ₂, χ₃}is represented by a following formula 26.

Note that, gray mapping is used for association of the QPSK symbol witha bit value.

[Expression 26]

x _(d)=√{square root over (E _(s)/2)}{(2c ₀−1)+j(2c ₁−1)}  (formula 26)

That is, in the case of {c₀, c₁}={0, 0}, a modulation point is χ₀, inthe case of {c₀, c₁}={0, 1}, the modulation point is χ₀, in the case of{c₀, c₁}={1, 0}, the modulation point is χ₀, and in the case of {c₀,c₁}={1, 1}, the modulation point is χ₀.

First, a formula of calculating the LLR of the bit c₀ using the channelestimation value h hat is derived based on a following formula 27.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 27} \right\rbrack & \; \\\begin{matrix}{z_{0} = {\ln \frac{p\left( {\left. y_{d} \middle| c_{0} \right. = 1} \right)}{p\left( {\left. y_{d} \middle| c_{0} \right. = 0} \right)}}} \\{= {\frac{2\sqrt{2E_{s}}}{N_{0}}{{Re}\left\lbrack {{\hat{h}}^{*}y_{d}} \right\rbrack}}} \\{= {\sqrt{\beta}\left( {{a}^{2} - {b}^{2}} \right)}}\end{matrix} & \left( {{formula}\mspace{14mu} 27} \right)\end{matrix}$

Here, a and b are independent Gaussian variables and are represented bya formula 28. Each of an average value μ_(a) and variance N_(a) of a isprovided by a formula 29, and each of an average value μ_(b) andvariance N_(b) of b is provided by a formula 30.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 28} \right\rbrack & \; \\\left\{ \begin{matrix}{a = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {\hat{h} + \frac{y_{d}}{\sqrt{E_{s}\beta}}} \right)}} \\{b = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {\hat{h} - \frac{y_{d}}{\sqrt{E_{s}\beta}}} \right)}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 28} \right) \\\left\lbrack {{Expression}\mspace{14mu} 29} \right\rbrack & \; \\\left\{ \begin{matrix}{{\mu_{a}\left( x_{d} \right)} = {{E\lbrack a\rbrack} = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {1 + \frac{x_{d}}{\sqrt{E_{s}\beta}}} \right)h}}} \\{N_{a} = {{V\lbrack a\rbrack} = \frac{\sqrt{2}}{\beta}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 29} \right) \\\left\lbrack {{Expression}{\mspace{11mu} \;}30} \right\rbrack & \; \\\left\{ \begin{matrix}{{\mu_{b}\left( x_{d} \right)} = {{E\lbrack b\rbrack} = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {1 - \frac{x_{d}}{\sqrt{E_{s}\beta}}} \right)h}}} \\{N_{b} = {{V\lbrack b\rbrack} = \frac{\sqrt{2}}{\beta}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 30} \right)\end{matrix}$

Here, a and b have the same variance, so that N_(a)=N_(b)=N_(ab) isprovided. When similar calculation to that of the formula 22 isperformed with the aforementioned average and variance, the modulationpoints with c₀=0 are χ₀ and χ₁ and the modulation points with c₀=1 areχ₂ and χ₃, so that a following formula 31 is obtained. The demodulationunit 407 uses the formula 31 as the formula of calculating the LLR ofthe bit c₀.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 31} \right\rbrack & \; \\\begin{matrix}{\lambda_{z,0} = {\ln \frac{\begin{matrix}{{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( \chi_{2} \right)}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{a}\left( \chi_{2} \right)}}}{N_{ab}} \right)}} +} \\{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( \chi_{3} \right)}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{a}\left( \chi_{3} \right)}}}{N_{ab}} \right)}}\end{matrix}}{\begin{matrix}{{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( \chi_{0} \right)}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{a}\left( \chi_{0} \right)}}}{N_{ab}} \right)}} +} \\{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( \chi_{1} \right)}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{a}\left( \chi_{1} \right)}}}{N_{ab}} \right)}}\end{matrix}}}} \\{= {\ln \frac{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( \chi_{2} \right)}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{a}\left( \chi_{2} \right)}}}{N_{ab}} \right)}}{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( \chi_{0} \right.}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{a}\left( \chi_{0} \right)}}}{N_{ab}} \right)}}}}\end{matrix} & \left( {{formula}\mspace{14mu} 31} \right)\end{matrix}$

Description has been given above for the bit c₀, and the bit c₁ will bethen described. In the demodulation unit 407, the LLR of the bit c₁ isprovided based on a following formula 32.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 32} \right\rbrack & \; \\\begin{matrix}{z_{1} = {\ln \frac{p\left( {\left. y_{d} \middle| c_{1} \right. = 1} \right)}{p\left( {\left. y_{d} \middle| c_{1} \right. = 0} \right)}}} \\{= {\frac{2\sqrt{2E_{s}}}{N_{0}}{{Im}\left\lbrack {{\hat{h}}^{*}y_{d}} \right\rbrack}}} \\{= {\sqrt{\beta}\left( {{a}^{2} - {b}^{2}} \right)}}\end{matrix} & \left( {{formula}\mspace{14mu} 32} \right)\end{matrix}$

Here, a and b are independent Gaussian variables and are represented bya formula 33. Each of an average value μ_(a) and variance N_(a) of a isprovided by a formula 34, and since the modulation points with c₁=0 areχ₀ and χ₂ and the modulation points with c₁=1 are χ₁ and χ₃, each of anaverage value μ_(b) and variance N_(b) of b is provided by a formula 35.Note that, j in the formula 33, the formula 34 and the formula 35 is animaginary unit.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 33} \right\rbrack & \; \\\left\{ \begin{matrix}{a = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {\hat{h} - {j\frac{y_{d}}{\sqrt{E_{s}\beta}}}} \right)}} \\{b = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {\hat{h} - {j\frac{y_{d}}{\sqrt{E_{s}\beta}}}} \right)}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 33} \right) \\\left\lbrack {{Expression}\mspace{14mu} 34} \right\rbrack & \; \\\left\{ \begin{matrix}{{\mu_{a}\left( x_{d} \right)} = {{E\lbrack a\rbrack} = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {1 - {j\frac{x_{d}}{\sqrt{E_{s}\beta}}}} \right)h}}} \\{N_{a} = {{V\lbrack a\rbrack} = \frac{\sqrt{2}}{\beta}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 34} \right) \\\left\lbrack {{Expression}{\mspace{11mu} \;}35} \right\rbrack & \; \\\left\{ \begin{matrix}{{\mu_{b}\left( x_{d} \right)} = {{E\lbrack b\rbrack} = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {1 + {j\frac{x_{d}}{\sqrt{E_{s}\beta}}}} \right)h}}} \\{N_{b} = {{V\lbrack b\rbrack} = \frac{\sqrt{2}}{\beta}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 35} \right)\end{matrix}$

Here, a and b have the same variance, so that N_(a)=N_(b)=N_(ab) isprovided. When similar calculation to that of the formula 22 isperformed with the aforementioned average and variance, a followingformula 36 is obtained. The demodulation unit 407 uses the formula 36 asthe formula of calculating the LLR of the bit c₁.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 36} \right\rbrack & \; \\\begin{matrix}{\lambda_{z,1} = {\ln \frac{\begin{matrix}{{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( \chi_{1} \right)}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{a}\left( \chi_{1} \right)}}}{N_{ab}} \right)}} +} \\{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( \chi_{3} \right)}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{a}\left( \chi_{3} \right)}}}{N_{ab}} \right)}}\end{matrix}}{\begin{matrix}{{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( \chi_{0} \right)}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{a}\left( \chi_{0} \right)}}}{N_{ab}} \right)}} +} \\{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( \chi_{2} \right)}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{a}\left( \chi_{2} \right)}}}{N_{ab}} \right)}}\end{matrix}}}} \\{= {\ln \frac{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( \chi_{1} \right)}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{a}\left( \chi_{1} \right)}}}{N_{ab}} \right)}}{{I_{0}\left( \frac{2{a}{{\mu_{a}\left( \chi_{0} \right.}}}{N_{ab}} \right)}{I_{0}\left( \frac{2{b}{{\mu_{a}\left( \chi_{0} \right)}}}{N_{ab}} \right)}}}}\end{matrix} & \left( {{formula}\mspace{14mu} 36} \right)\end{matrix}$

In this manner, the modulation unit 407 is able to calculate the LLR ofeach of the bits (c₀ and c₁) of the QPSK with the formula 31 and theformula 36. The similar is applicable also to a case where othermodulation methods such as 16QPSK and 16QAM (Quadrature AmplitudeModulation) are used.

Modified Example 2

Description has been given in the aforementioned embodiment and themodified example 1 thereof for a case where the channel estimation unit406 uses the LS channel estimation as the channel estimation method.However, a new LLR calculation method using a channel estimation valueis used in the present embodiment and the modified example thereof, butthe channel estimation method may be any one without limitation to theLS channel estimation. Thus, as another channel estimation method, anLLR calculation method when channel estimation with a noise eliminated(NE) reference, which has been conventionally and commonly used as thechannel estimation method, will be described.

First, the channel estimation with the NE reference performed by thechannel estimation unit 406 will be described. When a complex channelgain of a channel is H(k) similarly to the formula 1, for example, inOFDM transmission, a channel vector H is represented by a formula 37. Avector of an LS channel estimation value H_(LS) obtained by the LSchannel estimation is represented by a formula 38. Time responses(impulse responses) h and h_(LS) of H and H_(LS) are represented by aformula 39. Here, F is a DFT matrix of N points.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 37} \right\rbrack & \; \\{H = \left\lbrack \begin{matrix}{H(0)} & {H(1)} & \ldots & \left. {H\left( {K - 1} \right)} \right\rbrack^{T}\end{matrix} \right.} & \left( {{formula}\mspace{14mu} 37} \right) \\\left\lbrack {{Expression}\mspace{14mu} 38} \right\rbrack & \; \\{{\hat{H}}_{LS} = \left\lbrack \begin{matrix}{{\hat{H}}_{LS}(0)} & {{\hat{H}}_{LS}(1)} & \ldots & \left. {{\hat{H}}_{LS}\left( {K - 1} \right)} \right\rbrack^{T}\end{matrix} \right.} & \left( {{formula}\mspace{14mu} 38} \right) \\\left\lbrack {{Expression}{\mspace{11mu} \;}39} \right\rbrack & \; \\\left\{ \begin{matrix}{h = {\frac{1}{K}F^{H}H}} \\{{\, h_{LS}} = {\frac{1}{K}F^{H}{\hat{H}}_{LS}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 39} \right)\end{matrix}$

In the channel estimation with the NE reference, by performing filteringof a following formula for the impulse responses obtained by the LSchannel estimation, an impulse response vector h_(NE) from which noisehas been eliminated is obtained.

[Expression 40]

ĥ _(NE) =Wĥ _(LS)  (formula 40)

Here, a filter W is a matrix of K×K in which diagonal elements from 1 toL are 1 and other elements are 0. L is desirably the number of channelpaths, but when the number of paths is not able to be estimated, is setas a given length such as CP (or guard interval). Further, the elementdoes not need to be 1, and, for example, when there is a guard band, itis also possible to perform weighting in consideration of the guardband. By converting the obtained impulse response vector h_(NE) fromwhich noise is eliminated into a frequency domain, a channel estimationvector H_(NE) from which noise is eliminated is obtained.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 41} \right\rbrack & \; \\\begin{matrix}{{\hat{H}}_{NE} = {F{\hat{h}}_{NE}}} \\{= {{FWF}^{H}{\hat{h}}_{LS}}} \\{= \begin{bmatrix}{{\hat{H}}_{NE}(0)} & {{\hat{H}}_{NE}(1)} & \ldots & {{\hat{H}}_{NE}\left( {K - 1} \right)}\end{bmatrix}^{T}}\end{matrix} & \left( {{formula}\mspace{14mu} 41} \right)\end{matrix}$

In the channel estimation with the NE reference, power of noise is ableto be suppressed according to the number of elements of 1 included inthe filter W. For example, when the number of elements of 1 is L and asize of the filter W is K×K as described above, the power of noise isable to be suppressed to L/K. Accordingly, MSE of the channel estimationwith the NE reference is represented by a following formula 42. In thiscase, β is provided by a formula 43.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 42} \right\rbrack & \; \\{\sigma_{est}^{2} = {\frac{L}{K}\frac{N_{0}}{E_{p}}}} & \left( {{formula}\mspace{14mu} 42} \right) \\\left\lbrack {{Expression}\mspace{14mu} 43} \right\rbrack & \; \\{\beta = {\frac{K}{L}\frac{E_{p}}{E_{s}}}} & \left( {{formula}\mspace{14mu} 43} \right)\end{matrix}$

By using the formula 43 instead of the formula 13 in the firstembodiment and additionally using H_(NE)(k) (hat) instead of h (hat),the demodulation unit 407 is able to suppress error included in the bitLLR also when the channel estimation unit 406 uses the channelestimation with the NE reference. Though shown above is a case where thediagonal elements from 1 to L are 1 and other elements are 0 in thefilter W, multiplication of a rectangle filter in a time domain isequivalent to convolutional computation of a sine function in afrequency domain. That is, the channel estimation with the NE referencemay be called weighted averaging processing in the frequency domain.Improvement of accuracy of channel estimation by averaging may beperformed also in an antenna direction when there is a correlation notonly with a frequency, but with a time, a code or an antenna.

Even when a channel estimation method other than one with the LSreference or the NE reference is used, by theoretically calculating avalue of mean square error MSE of the channel estimation value h (hat)or holding a value which is empirically obtained by simulation or thelike to calculate β with the value, the LLR calculation method describedabove is applicable to cases where any channel estimation method isused. Note that, like the present embodiment and the modified example, βmay be calculated without directly obtaining the mean square error MSEof the channel estimation value h (hat), but by substituting E_(s),E_(p), N₀ and the like into a formula obtained by substituting a formulaof calculating the MSE into a definition formula of β, or a value of βaccording to a combination of values of E_(s), E_(p), N₀ and the likemay be obtained in advance by simulation or the like and stored to usethe value.

Results of simulation of a calculator with the LLR calculation method ofthe present embodiment are shown in FIG. 6 and FIG. 7.

FIG. 6 shows results of simulation when the channel estimation with theLS reference is used as the channel estimation, and FIG. 7 shows resultsof simulation when the channel estimation with the NE reference is usedas the channel estimation. In FIG. 6, a horizontal axis indicates anaverage transmission power spectral density E_(s)/average noise spectraldensity N₀ (dB) and a vertical axis indicates a frame error rate (FER).As conditions of the simulation, it is set that subcarriers are 64, a CPlength has 16 points, a modulation method is the QPSK, an errorcorrection code is a turbo code with a coding rate of 1/2 and aconstraint length of 4, a decoder is Max-Log-MAP decoding with acorrection term having the iteration number of 8, and a channel model isRayleigh fading having 12 paths with an attenuation constant of 2 dB.Further, a frame composition is set as not one of FIG. 3 but one inwhich one frame is composed of 1 pilot ODFM symbol and 16 data OFDMsymbols. In FIG. 6 and FIG. 7, a plot with crosses (+) indicates a casewhere channel estimation is complete, triangles (▴) show performancewhen the conventional LLR calculation method is used, and circles (◯)show performance when the LLR calculation method of the presentembodiment is used.

The LLR calculation method of the present embodiment has an improvementeffect of 0.4 dB in FER=0.01 compared to the conventional one accordingto FIG. 6 in which the LS channel estimation is performed, and has animprovement effect of 0.15 dB according to FIG. 7 in which the NEchannel estimation is performed. In this manner, it is possible toconfirm that the LLR calculation method of the present embodiment has aneffect of improvement in transmission performance.

Second Embodiment

In the first embodiment, a case where data is demodulated by a channelestimation value obtained by a reference signal and further decoded hasbeen described. Incidentally, decision-feedback channel estimation(iterative channel estimation) is effective that when reliability ofdata after decoding is high, a data signal is regarded as a referencesignal and channel estimation is performed again. By applying theiterative channel estimation, the data signal is able to be handled asthe reference signal. As a result thereof, the number of referencesignals apparently increases and accuracy of the channel estimation isable to be improved significantly, which is a reason of being effective.Note that, though description will be given by exemplifying the case ofapplying to downlink of LTE, that is, OFDM transmission in the presentembodiment as well, similarly to the first embodiment, applying to anycommunication systems is possible as long as being a system performingchannel estimation.

A base station device 101 in the present embodiment may have the sameconfiguration as the configuration of the base station of the firstembodiment, so that description thereof will be omitted. A signaltransmitted by the base station device 101 is received by a terminaldevice 102 a. FIG. 8 is a schematic block diagram showing an example ofa configuration of a receiver of the terminal device 102 a in thepresent embodiment. The terminal device 102 a is constituted byincluding a receive antenna 401, a radio reception unit 402, a CPremoval unit 403, an FFT (Fast Fourier Transform) unit 404, a datasignal extraction unit 405, a channel estimation unit 406 a, ademodulation unit 407 a, a de-interleave unit 408, a decoding unit 409a, an interleave unit 801, a replica generation unit 802, a replicaabsolute value correction unit 803, a reference signal generation unit804, and a frame composition unit 805. Note that, in addition to each ofthe units, the terminal device 102 a is constituted by including aconfiguration that a terminal device which performs radio communicationwith a base station device generally has, such as a transmission unitthat transmits a radio signal to the base station device 101, butillustration and description thereof will be omitted here.

A signal transmitted from the base station device 101 is received by thereceive antenna 401 of the terminal device 102 a. Note that, theterminal device 102 a has one receive antenna in the present embodiment,but may have a plurality of receive antennas and a publicly knowntechnique such as receive antenna diversity may be applied. The signalreceived by the receive antenna is input to the radio reception unit402. The radio reception unit 402 applies down-conversion, bandrestriction filtering, A/D (Analog-to-Digital) conversion and the liketo the input signal.

An output of the radio reception unit 402 is input to the CP removalunit 403. The CP removal unit 403 partitions the received signal foreach of (N_(FFT)+N_(CP)) points, and removes N_(CP) points from a headof the received signal of (N_(FFT)+N_(CP)) points. A signal for each ofN_(FFT) points, which is output by the CP removal unit 403, is input tothe FFT unit 404. The FFT unit 404 applies FFT of N_(FFT) points tothereby perform transformation from a time domain signal for each ofN_(FFT) points, which is input, into a frequency domain signal (receivedfrequency domain signal). An output of the FFT unit 404 is input to thedata signal extraction unit 405 and the channel estimation unit 406 a.

The data signal extraction unit 405 extracts a received data signal fromthe received frequency domain signal in accordance with the framecomposition of FIG. 3 to input to the demodulation unit 407 a. Thedemodulation unit 407 a uses a channel estimation value input from thechannel estimation unit 406 a to apply processing of compensating for aninfluence of a channel and transforming a symbol sequence after thechannel compensation into a sequence of a bit LLR to the received datasignal input from the data signal extraction unit 405. Channelcompensation by using an average noise power spectral density input withthe channel estimation value from the channel estimation unit 406 a (forexample, with an MMSE reference) may be performed. Processing performedby the demodulation unit 407 a in the present embodiment will bedescribed below in detail.

An LLR output by the demodulation unit 407 a is input to thede-interleave unit 408, and subjected to processing of de-interleavingthe interleave having been applied in the interleave unit 202 of thebase station device 101. An output of the de-interleave unit 408 isinput to the decoding unit 409 a, and the decoding unit 409 a performsdecoding similarly to the decoding unit 409 in the first embodimentbased on error correction coding applied at the base station device 101.A posteriori LLR of coded bits obtained by decoding processing is inputto the interleave unit 801. The LLR input to the interleave unit 801 maybe an external LLR. When the decoding unit 409 a inputs the posterioriLLR of the coded bits to the interleave unit 801, the terminal device102 a performs iterative channel estimation, but when a condition ofterminating iteration, such as when the predetermined iteration numberis reached, is satisfied, the decoding unit 409 a outputs ahard-decision result of decoding processing as a restored bit sequenceT.

The interleave unit 801 applies sorting processing same as that of theinterleave unit 202 of the base station device 101 to the LLR of thecoded bits, which is input from the decoding unit 409 a, and inputs theLLR of the coded bits after interleaving to the replica generation unit802. The replica generation unit 802 generates a symbol replica (softreplica) of a transmission signal by the LLR of the coded bits, which isinput, and a modulation method applied at the modulation unit 203 of thebase station device 101 to input to the replica absolute valuecorrection unit 803.

The replica absolute value correction unit 803 corrects an absolutevalue of the input symbol replica, and inputs the corrected symbolreplica to the frame composition unit 805. For example, the replicaabsolute value correction unit 803 sets a size of the symbol replica asa given value (for example, 1) when, for example, an absolute value ofthe symbol replica is a predetermined value (threshold) or more, andsets the size of the symbol replica as 0 when the absolute value of thesymbol replica is smaller than the predetermined value. The replicaabsolute value correction unit 803 corrects the size of the symbolreplica, so that a symbol replica having low likelihood is not used forchannel estimation. As a result thereof, it is possible to preventdeterioration of accuracy of the channel estimation.

Note that, the size of the symbol replica is set as 0 when the absolutevalue of the symbol replica is smaller than the predetermined value inthe example above, but without setting as 0, a symbol replica whoseabsolute value is smaller than the predetermined value may be deletedand only a symbol replica whose absolute value is larger than thepredetermined value may be input to the frame composition unit 805.Moreover, though described in the present embodiment is a case where onepredetermined value is prepared to quantize the symbol replica toamplitude of binary of 0 and 1, a plurality of predetermined values maybe prepared to perform processing of quantizing to amplitude of ternaryor more, or the replica absolute value correction unit 803 may notcorrect the absolute value, that is, the soft replica may be also usedas it is. The corrected symbol replica is input to the frame compositionunit 805.

The reference signal generation unit 804 generates a reference signalsame as that of the reference signal generation unit 204 of the basestation device 101. The frame composition unit 805 composes a frame witha frame composition similar to that of the frame composition unit 205 ofthe base station device 101 (For example, FIG. 3) by using the referencesignal input from the reference signal generation unit 804 and thereplica input from the replica absolute value correction unit 803. Thecomposed frame is input to the channel estimation unit 406 a and thedemodulation unit 407 a. The channel estimation unit 406 a performschannel estimation by using the received frequency domain signal inputfrom the FFT unit 404. The channel estimation unit 406 a performschannel estimation in the first time of iterative channel estimation bycomparing a reference signal in the received frequency domain signal tothe reference signal which is arranged in the frame input from the framecomposition unit 805. However, in the second and subsequent times of theiterative channel estimation, the channel estimation unit 406 a performschannel estimation by comparing the reference signal and a data signalin the received frequency domain signal to a replica of the referencesignal and a data signal arranged in the frame input from the framecomposition unit 805.

The channel estimation in the second and subsequent times of theiterative channel estimation will be described in detail. First, whenthe transmission frame composition as shown in FIG. 3 is assumed and areceived signal in a k-th subcarrier of an m-th OFDM symbol isY^((m))(k), a received signal sequence Y(k) in the k-th subcarrier isrepresented by a following formula 44.

[Expression 44]

Y(k)=[Y ⁽¹⁾(k)Y ⁽²⁾(k) . . . Y ⁽¹⁴⁾(k)]^(T)  (formula 44)

For example, in the case of k=3, Y⁽⁴⁾(3) and Y⁽¹¹⁾(3) are receivedreference signals and other elements serve as received data signals. Thesimilar is applied also to other subcarriers, so that an index of k willbe omitted and lowercase letters will be used below in order to simplifythe description. Thus, the formula 44 is represented like a followingformula 45.

[Expression 45]

y=[y ⁽¹⁾ y ⁽²⁾ . . . y ⁽¹⁴⁾]^(T)  (formula 45)

The channel estimation unit 406 a performs calculation with a followingformula 46 to thereby calculate a channel estimation value h (hat) ineach subcarrier. Here, x (hat) represents a replica of a transmissionsignal, and in an OFDM signal for transmitting a reference signal, thereference signal is input and a relational formula of a formula 47 issatisfied.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 46} \right\rbrack & \; \\{\hat{h} = {{\hat{x}}^{+}y}} & \left( {{formula}\mspace{14mu} 46} \right) \\\left\lbrack {{Expression}\mspace{14mu} 47} \right\rbrack & \; \\\left\{ \begin{matrix}{\hat{x} = \begin{bmatrix}{\hat{x}}^{(1)} & {\hat{x}}^{(2)} & \ldots & {\hat{x}}^{(7)}\end{bmatrix}} \\{{\hat{x}}^{+} = {\frac{1}{E_{p} + {\hat{M}E_{s}}}\begin{bmatrix}{\hat{x}}^{{(1)}^{*}} & {\hat{x}}^{{(2)}^{*}} & \ldots & {\hat{x}}^{{(7)}^{*}}\end{bmatrix}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 47} \right)\end{matrix}$

In the formula 47, M (hat) is the number of non-zero elements of a datasymbol of x (hat) (maximum, 7). In this manner, the channel estimationunit 406 a of the present embodiment performs channel estimation byusing many received data signals when there are many replicas whoseabsolute value is large in the replicas input to the replica absolutevalue correction unit 803, thus making it possible to perform channelestimation with high accuracy. On the other hand, for example, whenthere is no replica whose absolute value is large, channel estimation isperformed by using only a reference signal, so that deterioration inaccuracy of channel estimation due to decision error of data is able tobe suppressed.

Note that, since it is assumed that there is no time variation of achannel in the formula 46, all symbols are subjected to equal gaincombining and one channel estimation value is calculated, but when thereis time variation of a channel, a channel estimation value for each OFDMsymbol may be calculated by performing not the equal gain combining butweighting combining. For example, any of averaging of only adjacentsymbols, weighting with MSE being minimum, weighting with a sincfunction or a Bessel function of the first kind and zero order may beused.

Further, the channel estimation unit 406 a calculates average noisepower in addition to the channel estimation value. A calculation methodthereof may be any one. For example, in estimation of the average noisepower, calculation may be performed by using reception power in asubcarrier in which none is transmitted (null-subcarrier), orcalculation may be performed by, in a resource element in which areference signal is received, subtracting a value obtained bymultiplying the transmitted reference signal by a channel estimationvalue from the received signal. The channel estimation value and anaverage noise power spectral density, which are calculated by thechannel estimation unit 406 a, are input to the demodulation unit 407 aand the decoding unit 409 a.

Next, processing at the demodulation unit 407 a, which is acharacteristic of the present embodiment, will be described. Calculationof an LLR of the m-th OFDM symbol by using BPSK in the modulation unit407 a is performed based on a following formula 48 by using the channelestimation value input from the channel estimation unit 406 a.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 48} \right\rbrack & \; \\{z = {{\frac{4\sqrt{E_{s}}}{N_{0}}{{Re}\left\lbrack {{\hat{h}}^{*}y^{(m)}} \right\rbrack}} = {\sqrt{\beta}\left( {{a^{(m)}}^{2} - {b^{(m)}}^{2}} \right)}}} & \left( {{formula}\mspace{14mu} 48} \right)\end{matrix}$

Here, a^((m)) and b^((m)) are independent Gaussian variables, andrepresented by a formula 49. Here, an average value μ_(a) of a and anaverage value μ_(b) of b in the formula 49 are provided by a formula 50,variance N_(a) of a and variance N_(b) of b are provided by a formula51. Note that, x^((m)) (hat) in the formulas 51 and 52 is an m-th OFDMsymbol in the frame generated by the frame composition unit 805.

$\begin{matrix}{\mspace{79mu} \left\lbrack {{Expression}\mspace{14mu} 49} \right\rbrack} & \; \\{\mspace{79mu} \left\{ \begin{matrix}{a^{(m)} = {\sqrt{\gamma}\left( {\hat{h} + \frac{y^{(m)}}{\sqrt{E_{s}\beta}}} \right)}} \\{b^{(m)} = {\sqrt{\gamma}\left( {\hat{h} - \frac{y^{(m)}}{\sqrt{E_{s}\beta}}} \right)}}\end{matrix} \right.} & \left( {{formula}\mspace{14mu} 49} \right) \\{\mspace{79mu} \left\lbrack {{Expression}\mspace{14mu} 50} \right\rbrack} & \; \\{\mspace{79mu} \left\{ \begin{matrix}{{\mu_{a}\left( x^{(m)} \right)} = {{E\lbrack a\rbrack} = {\sqrt{\gamma}\left( {1 + \frac{x^{(m)}}{\sqrt{E_{s}\beta}}} \right)h}}} \\{{\mu_{b}\left( x^{(m)} \right)} = {{E\lbrack b\rbrack} = {\sqrt{\gamma}\left( {1 - \frac{x^{(m)}}{\sqrt{E_{s}\beta}}} \right)h}}}\end{matrix} \right.} & \left( {{formula}\mspace{14mu} 50} \right) \\{\mspace{79mu} \left\lbrack {{Expression}\mspace{14mu} 51} \right\rbrack} & \; \\\begin{matrix}{N_{a}^{(m)} = {{V\left\lbrack a^{(m)} \right\rbrack} = {E\left\lbrack {{a^{(m)} - {\mu_{a}\left( x^{(m)} \right)}}}^{2} \right\rbrack}}} \\{= {{E\left\lbrack {{{\sqrt{\gamma}\left( {\hat{h} + \frac{y^{(m)}}{\sqrt{E_{s}\beta}}} \right)} - {\mu_{a}\left( x^{(m)} \right)}}}^{2} \right\rbrack} =}} \\{{E\left\lbrack {{{\sqrt{\gamma}\left( {{{\hat{x}}^{+}y} + \frac{y^{(m)}}{\sqrt{E_{s}\beta}}} \right)} - {\mu_{a}\left( x^{(m)} \right)}}}^{2} \right\rbrack}} \\{= {E\left\lbrack {{{\sqrt{\gamma}\left( {1 + \frac{x^{(m)}}{\sqrt{E_{s}\beta}}} \right)h} + {{\hat{x}}^{+}n} + \frac{n^{(m)}}{\sqrt{E_{s}\beta}} - {\mu_{a}\left( x^{(m)} \right)}}}^{2} \right\rbrack}} \\{= {{E\left\lbrack {\gamma {{{{\hat{x}}^{+}n} + \frac{n^{(m)}}{\sqrt{E_{s}\beta}}}}^{2}} \right\rbrack} = {E\left\lbrack {\frac{E_{s}}{N_{0}}{{\left( {{\hat{x}}^{+} + \frac{e^{(m)}}{\sqrt{E_{s}\beta}}} \right)n}}^{2}} \right\rbrack}}} \\{= {{E\left\lbrack {E_{s}{{{\hat{x}}^{+} + \frac{e^{(m)}}{\sqrt{E_{s}\beta}}}}^{2}} \right\rbrack} = {\frac{2}{\beta}\left( {1 + {\sqrt{\frac{1}{E_{s}\beta}}{{Re}\left\lbrack {\hat{x}}^{(m)} \right\rbrack}}} \right)}}}\end{matrix} & \left( {{formula}\mspace{14mu} 51} \right) \\{\mspace{79mu} \left\lbrack {{Expression}\mspace{14mu} 52} \right\rbrack} & \; \\{\mspace{79mu} {N_{b}^{(m)} = {\frac{2}{\beta}\left( {1 - {\sqrt{\frac{1}{E_{s}\beta}}{{Re}\left\lbrack {\hat{x}}^{(m)} \right\rbrack}}} \right)}}} & \left( {{formula}\mspace{14mu} 52} \right)\end{matrix}$

With the above average and variance, and a following formula 53, the bitLLR is able to be calculated similarly to the first embodiment. Notethat, e^((m)) is a row vector with one row and seven columns, in whichan m-th element is 1 and other elements are 0, and n is a noisecomponent vector (seven rows and one column) in each reception symbol.

$\begin{matrix}{\mspace{79mu} \left\lbrack {{Expression}\mspace{14mu} 53} \right\rbrack} & \; \\\begin{matrix}{\lambda_{z}^{(m)} = {\ln \frac{p\left( {\left. z \middle| m^{(m)} \right. = {+ 1}} \right)}{p\left( {\left. z \middle| x^{(m)} \right. = {- 1}} \right)}}} \\{= {\ln \frac{\begin{matrix}{\exp \left( {- \frac{{{\mu_{a}\left( {+ \sqrt{E_{s}}} \right)}}^{2}}{N_{a}^{(m)}}} \right){I_{0}\left( \frac{2{a^{(m)}}{{\mu_{a}\left( {+ \sqrt{E_{s}}} \right)}}^{2}}{N_{a}^{(m)}} \right)}} \\{\exp \left( {- \frac{{{\mu_{b}\left( {+ \sqrt{E_{s}}} \right)}}^{2}}{N_{b}^{(m)}}} \right){I_{0}\left( \frac{2{b^{(m)}}{{\mu_{b}\left( {+ \sqrt{E_{s}}} \right)}}^{2}}{N_{b}^{(m)}} \right)}}\end{matrix}}{\begin{matrix}{\exp \left( {- \frac{{{\mu_{a}\left( {+ \sqrt{E_{s}}} \right)}}^{2}}{N_{a}^{(m)}}} \right){I_{0}\left( \frac{2{a^{(m)}}{{\mu_{a}\left( {- \sqrt{E_{s}}} \right)}}^{2}}{N_{a}^{(m)}} \right)}} \\{\exp \left( {- \frac{{{\mu_{b}\left( {- \sqrt{E_{s}}} \right)}}^{2}}{N_{b}^{(m)}}} \right){I_{0}\left( \frac{2{b^{(m)}}{{\mu_{b}\left( {- \sqrt{E_{s}}} \right)}}^{2}}{N_{b}^{(m)}} \right)}}\end{matrix}}}} \\{= {\frac{{{\mu_{a}\left( {- \sqrt{E_{s}}} \right)}}^{2}}{N_{a}^{(m)}} + \frac{{{\mu_{b}\left( {- \sqrt{E_{s}}} \right)}}^{2}}{N_{b}^{(m)}} - \frac{{{\mu_{a}\left( {- \sqrt{E_{s}}} \right)}}^{2}}{N_{a}^{(m)}} -}} \\{{\frac{{{\mu_{b}\left( {- \sqrt{E_{s}}} \right)}}^{2}}{N_{b}^{(m)}} +}} \\{{\ln \frac{{I_{0}\left( \frac{2{a^{(m)}}{{\mu_{a}\left( {+ \sqrt{E_{s}}} \right)}}^{2}}{N_{a}^{(m)}} \right)}{I_{0}\left( \frac{2{b^{(m)}}{{\mu_{b}\left( {+ \sqrt{E_{s}}} \right)}}^{2}}{N_{b}^{(m)}} \right)}}{{I_{0}\left( \frac{2{a^{(m)}}{{\mu_{a}\left( {- \sqrt{E_{s}}} \right)}}^{2}}{N_{a}^{(m)}} \right)}{I_{0}\left( \frac{2{b^{(m)}}{{\mu_{b}\left( {- \sqrt{E_{s}}} \right)}}^{2}}{N_{b}^{(m)}} \right)}}}}\end{matrix} & \left( {{formula}\mspace{14mu} 53} \right)\end{matrix}$

That is, the demodulation unit 407 a performs computation of the formula53 by using the data signal, the reference signal, the average noisepower spectral density and the channel estimation value, which are inputfrom the channel estimation unit 406 a, the received signal input fromthe data signal extraction unit 405, and the symbol input from the framecomposition unit 805, and performs output as the bit LLR to thede-interleave unit 408. For example, in a case where the channelestimation method is the LS channel estimation, power capable of beingused for channel estimation is E_(p) when iteration is not made, whileit is possible to increase the power by the number of pieces of datasubjected to hard decision, so that channel estimation error (MSE)becomes as shown in a formula 54.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 54} \right\rbrack & \; \\{\sigma_{est}^{2} = \frac{N_{0}}{E_{p} + {\hat{M}\; E_{s}}}} & \left( {{formula}\mspace{14mu} 54} \right) \\\left\lbrack {{Expression}\mspace{14mu} 55} \right\rbrack & \; \\{\beta = \frac{E_{p} + {\hat{M}\; E_{s}}}{E_{s}}} & \left( {{formula}\mspace{14mu} 55} \right)\end{matrix}$

Here, though decision error at the time of hard decision is notconsidered in the formula 54, correction may be performed by consideringa parameter such as an empirical error rate. A soft-decision value maybe used for making the decision error less vulnerable.

As above, the terminal device 102 a in the present embodiment is able toimprove accuracy of channel estimation by using the iterative channelestimation as well as to suppress error included in the bit LLR which isa result of demodulation processing. By performing error decision anderror correction decoding by using the LLR, it is possible to improve abit error rate compared to a case where the conventional LLR calculationmethod is used.

Description has been given in the present embodiment by exemplifying themethod for using the LLR of data only for channel estimation. When thereis interference such as inter-symbol interference or inter-streaminterference in MIMO, however, processing of using the LLR of data forchannel estimation and also for generation of a replica of theinterference for subtracting from a received signal, thereby cancellingthe interference may be applied.

Modified Example 1

Though a case where BPSK is used as the modulation method has beendescribed above, description will be given as a modified example 1 forprocessing of the modulation unit 407 a when the modulation method ofdata is the QPSK in the iterative channel estimation, that is, themodulation unit 203 generates a modulation symbol by the QPSK. When themodulation method is the QPSK, two bits forming a QPSK symbol arerespectively c0 and c1. In this case, a transmission data symbolx_(d)ε{χ₀, χ₁, χ₂, χ₃} is represented by a following formula 56.

[Expression 56]

x _(d)=√{square root over (E _(s)/2)}{(2c ₀−1)+j(2c ₁−1)}  (formula 56)

A bit LLR of c₀ in an m-th OFDM symbol of a k-th subcarrier at the timeof iterative channel estimation is able to be put as shown in afollowing formula 57.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 57} \right\rbrack & \; \\\begin{matrix}{z_{0}^{(m)} = {\ln \; \frac{p\left( {\left. y^{(m)} \middle| c_{0} \right. = 1} \right)}{p\left( {\left. y^{(m)} \middle| c_{0} \right. = 0} \right)}}} \\{= {\frac{2\sqrt{2E_{s}}}{N_{0}}{{Re}\left\lbrack {{\hat{h}}^{*}y^{(m)}} \right\rbrack}}} \\{= {\sqrt{\beta}\left( {{a^{(m)}}^{2} - {b^{(m)}}^{2}} \right)}}\end{matrix} & \left( {{formula}\mspace{14mu} 57} \right)\end{matrix}$

Here, a^((m)) and b^((m)) are independent Gaussian variables, andrepresented by a formula 58. Here, an average value μ_(a) and varianceN_(a) of a^((m)) are provided by a formula 59, and an average valueμ_(b) and variance N_(b) of b^((m)) are represented by a formula 60.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 58} \right\rbrack & \; \\\left\{ \begin{matrix}{a^{(m)} = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {\hat{h} + \frac{y^{(m)}}{\sqrt{E_{s}\beta}}} \right)}} \\{b^{(m)} = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {\hat{h} - \frac{y^{(m)}}{\sqrt{E_{s}\beta}}} \right)}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 58} \right) \\\left\lbrack {{Expression}\mspace{14mu} 59} \right\rbrack & \; \\\left\{ \begin{matrix}{{\mu_{a}\left( x_{d} \right)} = {{E\lbrack a\rbrack} = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {1 + \frac{x^{(m)}}{\sqrt{E_{s}\beta}}} \right)h}}} \\{N_{a} = {{V\lbrack a\rbrack} = {\frac{\sqrt{2}}{\beta}\left( {1 + {\sqrt{\frac{1}{E_{s}\beta}}{{Re}\left\lbrack {\hat{x}}^{(m)} \right\rbrack}}} \right)}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 59} \right) \\\left\lbrack {{Expression}\mspace{14mu} 60} \right\rbrack & \; \\\left\{ \begin{matrix}{{\mu_{b}\left( x_{d} \right)} = {{E\lbrack b\rbrack} = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {1 - \frac{x^{(m)}}{\sqrt{E_{s}\beta}}} \right)h}}} \\{N_{b} = {{V\lbrack b\rbrack} = {\frac{\sqrt{2}}{\beta}\left( {1 - {\sqrt{\frac{1}{E_{s}\beta}}{{Re}\left\lbrack {\hat{x}}^{(m)} \right\rbrack}}} \right)}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 60} \right)\end{matrix}$

With the above average and variance, a following formula 61 is obtainedsimilarly to calculation of the formula 53. The demodulation unit 407 auses the formula 61 as formula of calculating the LLR of the bit c₀.Here, f(x_(q)) in the formula 61 is represented by a formula 62.

$\begin{matrix}{\mspace{20mu} \left\lbrack {{Expression}\mspace{14mu} 61} \right\rbrack} & \; \\{\mspace{20mu} {\lambda_{z,0}^{(m)} = {{\ln \; \frac{{f\left( \chi_{2} \right)} + {f\left( \chi_{3} \right)}}{{f\left( \chi_{0} \right)} + {f\left( \chi_{1} \right)}}} = {\ln \; \frac{f\left( \chi_{2} \right)}{f\left( \chi_{0} \right)}}}}} & \left( {{formula}\mspace{14mu} 61} \right) \\{\mspace{20mu} \left\lbrack {{Expression}\mspace{14mu} 62} \right\rbrack} & \; \\{{f\left( X_{q} \right)} = {{\exp \left( {{- \frac{{{\mu_{a}\left( \chi_{q} \right)}}^{2}}{N_{a}^{(m)}}} - \frac{{{\mu_{b}\left( \chi_{q} \right)}}^{2}}{N_{b}^{(m)}}} \right)}{I_{0}\left( \frac{2{a^{(m)}}{{\mu_{a}\left( \chi_{q} \right)}}^{2}}{N_{a}^{(m)}} \right)}{I_{0}\left( \frac{2{b^{(m)}}{{\mu_{b}\left( \chi_{q} \right)}}^{2}}{N_{b}^{(m)}} \right)}}} & \left( {{formula}\mspace{14mu} 62} \right)\end{matrix}$

Next, the bit c₁ will be described. A bit LLR of c₁ in the m-th OFDMsymbol of the k-th subcarrier at the time of iterative channelestimation is able to be put as shown in a following formula 63.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 63} \right\rbrack & \; \\\begin{matrix}{z_{1}^{(m)} = {\ln \; \frac{p\left( {\left. y^{(m)} \middle| c_{1} \right. = 1} \right)}{p\left( {\left. y^{(m)} \middle| c_{1} \right. = 0} \right)}}} \\{= {\frac{2\sqrt{2E_{s}}}{N_{0}}{{Im}\left\lbrack {{\hat{h}}^{*}y^{(m)}} \right\rbrack}}} \\{= {\sqrt{\beta}\left( {{a^{(m)}}^{2} - {b^{(m)}}^{2}} \right)}}\end{matrix} & \left( {{formula}\mspace{14mu} 63} \right)\end{matrix}$

Here, a^((m)) and b^((m)) are independent Gaussian variables, andrepresented by a formula 64. An average value μ_(a) and variance N_(a)of a^((m)) are provided by a formula 65, and an average value μ_(b) andvariance N_(b) of b^((m)) are provided by a formula 66.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 64} \right\rbrack & \; \\\left\{ \begin{matrix}{a^{(m)} = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {\hat{h} - {j\; \frac{y^{(m)}}{\sqrt{E_{s}\beta}}}} \right)}} \\{b^{(m)} = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {\hat{h} + {j\; \frac{y^{(m)}}{\sqrt{E_{s}\beta}}}} \right)}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 64} \right) \\\left\lbrack {{Expression}\mspace{14mu} 65} \right\rbrack & \; \\\left\{ \begin{matrix}{{\mu_{a}\left( x_{d} \right)} = {{E\lbrack a\rbrack} = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {h - {j\; \frac{x^{(m)}}{\sqrt{E_{s}\beta}}}} \right)h}}} \\{N_{a} = {{V\lbrack a\rbrack} = {\frac{\sqrt{2}}{\beta}\left( {1 + {\sqrt{\frac{1}{E_{s}\beta}}{{Im}\left\lbrack {\hat{x}}^{(m)} \right\rbrack}}} \right)}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 65} \right) \\\left\lbrack {{Expression}\mspace{14mu} 66} \right\rbrack & \; \\\left\{ \begin{matrix}{{\mu_{a}\left( x_{d} \right)} = {{e\lbrack a\rbrack} = {2^{- \frac{1}{4}}\sqrt{\gamma}\left( {h - {j\; \frac{x^{(m)}}{\sqrt{E_{s}\beta}}}} \right)h}}} \\{N_{a} = {{V\lbrack a\rbrack} = {\frac{\sqrt{2}}{\beta}\left( {1 + {\sqrt{\frac{1}{E_{s}\beta}}{{Im}\left\lbrack {\hat{x}}^{(m)} \right\rbrack}}} \right)}}}\end{matrix} \right. & \left( {{formula}\mspace{14mu} 66} \right)\end{matrix}$

With the above average and variance, a following formula 67 is obtainedsimilarly to calculation of the formula 53. The demodulation unit 407uses the formula 67 as a formula of calculating the LLR of the bit c₁.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 67} \right\rbrack & \; \\{\lambda_{z,1}^{(m)} = {{\ln \; \frac{{f\left( \chi_{1} \right)} + {f\left( \chi_{3} \right)}}{{f\left( \chi_{0} \right)} + {f\left( \chi_{2} \right)}}} = {\ln \; \frac{f\left( \chi_{1} \right)}{f\left( \chi_{0} \right)}}}} & \left( {{formula}\mspace{14mu} 67} \right)\end{matrix}$

In this manner, the demodulation unit 407 a is able to calculate theLLRs of each of the bits (c₀ and c₁) of the QPSK by the formula 61 andthe formula 67, respectively. The similar is also applicable whenanother modulation method such as 16 QAM (Quadrature AmplitudeModulation) is used,

Modified Example 2

Description has been given in the second embodiment and the modifiedexample 1 thereof for the case where the LS channel estimation is usedas the channel estimation method during iterative channel estimation.However, a new LLR calculation method at the time of the iterativechannel estimation is used in the present embodiment, but the channelestimation method performed during the iterative channel estimation maybe any one without limitation to the LS channel estimation. Thus, asanother channel estimation method, an LLR calculation method whenchannel estimation with a noise eliminated (NE) reference will bedescribed.

The channel estimation with the NE reference itself has been describedin the modified example 2 of the first embodiment, so that descriptionthereof will be omitted. In the case of the LS channel estimation, achannel estimation error (MSE) in the iterative channel estimation isrepresented by the formula 54, and an influence of noise is able to beset as L/K in the channel estimation with the NE reference. That is, thechannel estimation error (MSE) in the channel estimation with the NEreference is represented by a formula 68. Accordingly, β is able to becalculated by a formula 69.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 68} \right\rbrack & \; \\{\sigma_{est}^{2} = {\frac{L}{K}\frac{N_{0}}{E_{p} + {\hat{M}\; E_{s}}}}} & \left( {{formula}\mspace{14mu} 68} \right) \\\left\lbrack {{Expression}\mspace{14mu} 69} \right\rbrack & \; \\{\beta = {\frac{K}{L}\frac{E_{p} + {\hat{M}E_{s}}}{E_{s}}}} & \left( {{formula}\mspace{14mu} 69} \right)\end{matrix}$

By using a value of the formula 69 instead of the formula 55, it ispossible to suppress error included in the bit LLR which is a result ofdemodulation processing at the time of the iterative channel estimationusing the NE channel estimation as well.

Third Embodiment

In the second embodiment, when channel estimation is performed, all datasequences obtained in previous demodulation were used. On the otherhand, the likelihood which has been obtained in the previousdemodulation is obtained also in next demodulation and is therefore notgenerally reflected on iteration, and an external LLR is exchangedbetween two decoders also in turbo decoding. Thus, described in a thirdembodiment is processing of the channel estimation unit 406 a andprocessing of the demodulation unit 407 a when an external replicasymbol is used in the iterative channel estimation. Note that, a framecomposition and the like in the present embodiment are similar to thoseof the second embodiment.

In the present embodiment, an external symbol replica is defined. Theexternal symbol replica x^((m)) (hat) which is used when a channelestimation value for an m-th OFDM is obtained is represented by afollowing formula 70.

[Expression 70])

{circumflex over (x)} _((m)) =[{circumflex over (x)} ⁽¹⁾ {circumflexover (x)} ₍₂₎ . . . {circumflex over (x)} ^((m−1))0{circumflex over (x)}^((m+1)) . . . {circumflex over (x)} ⁽⁷⁾]^(T)  (formula 70)

That is, a value of the x^((m)) (hat) is set as 0 in the formula 47.Thereby, the likelihood which has been obtained in previous demodulationis not to be used again in next demodulation. A vector of a followingformula 71 is calculated from the obtained external symbol replica. Inthe formula 71, M^((m)) (hat) is the number of non-zero elements of x(hat) (maximum, 13).

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 71} \right\rbrack & \; \\{{\hat{x}}^{{(m)} +} = {\frac{1}{E_{p} + {{\hat{M}}^{(m)}E_{s}}}{\hat{x}}^{{(m)}H}}} & \left( {{formula}\mspace{14mu} 71} \right)\end{matrix}$

As described above, since the value of x^((m)) (hat) is set as 0, avalue of variance is as shown in a following formula 72 with the formula65 and the formula 66.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 72} \right\rbrack & \; \\{N_{ab}^{(m)} = {{V\left\lbrack a^{(m)} \right\rbrack} = {{V\left\lbrack b^{(m)} \right\rbrack} = \frac{2}{\beta}}}} & \left( {{formula}\mspace{14mu} 72} \right)\end{matrix}$

Since a and b have the same variance, the LLR is represented by aformula 73. That is, the demodulation unit 407 a calculates the LLR byusing the formula 73.

$\begin{matrix}{\mspace{20mu} \left\lbrack {{Expression}\mspace{14mu} 73} \right\rbrack} & \; \\{\lambda_{z}^{(m)} = {\ln \; \frac{{I_{0}\left( \frac{2{a^{(m)}}{{\mu_{a}\left( {+ \sqrt{E_{s}}} \right)}}^{2}}{N_{a}^{(m)}} \right)}{I_{0}\left( \frac{2{b^{(m)}}{{\mu_{b}\left( {+ \sqrt{E_{s}}} \right)}}^{2}}{N_{b}^{(m)}} \right)}}{{I_{0}\left( \frac{2{a^{(m)}}{{\mu_{a}\left( {- \sqrt{E_{s}}} \right)}}^{2}}{N_{a}^{(m)}} \right)}{I_{0}\left( \frac{2{b^{(m)}}{{\mu_{b}\left( {- \sqrt{E_{s}}} \right)}}^{2}}{N_{b}^{(m)}} \right)}}}} & \left( {{formula}\mspace{14mu} 73} \right)\end{matrix}$

In this manner, simplification is attained in the above formula 73compared to the formula 53. For example, in the case of the LS channelestimation, the channel estimation unit 406 a calculates a channelestimation value by using a following formula 74.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 74} \right\rbrack & \; \\\begin{matrix}{{\hat{h}}_{LS}^{(m)} = {{\hat{x}}^{{(m)} +}y}} \\{= \left\{ \begin{matrix}{{{\frac{\hat{M}}{{\hat{M}}^{(m)}}{\hat{h}}_{LS}} - {\frac{1}{{\hat{M}}^{(m)}}\frac{y^{(m)}}{{\hat{x}}^{(m)}}}},} & \left( {{\hat{x}}^{(m)} \neq 0} \right) \\{{\hat{h}}_{LS},} & \left( {{\hat{x}}^{(m)} = 0} \right)\end{matrix} \right.}\end{matrix} & \left( {{formula}\mspace{14mu} 74} \right)\end{matrix}$

The above formula 74 shows that when the external symbol replica isused, the channel estimation value obtained from a data signal in them-th OFDM symbol may be merely subtracted from the channel estimationvalue used in the second embodiment. Moreover, a value of β^((m)) at thetime of the channel estimation of the m-th OFDM symbol is represented bya following formula 75.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 75} \right\rbrack & \; \\{\beta^{(m)} = \frac{E_{p} + {{\hat{M}}^{(m)}E_{s}}}{E_{s}}} & \left( {{formula}\mspace{14mu} 75} \right)\end{matrix}$

Further, when the channel estimation method is the channel estimationwith the NE reference, the channel estimation unit 406 a calculates thechannel estimation value by using a following formula 76.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 76} \right\rbrack & \; \\\begin{matrix}{{\hat{h}}_{LS}^{(m)} = {{\hat{x}}^{{(m)} +}y}} \\{= \left\{ \begin{matrix}{{{\frac{\hat{M}}{{\hat{M}}^{(m)}}{\hat{h}}_{LS}} - {\frac{1}{K{\hat{M}}^{(m)}}\frac{y^{(m)}}{{\hat{x}}^{(m)}}}},} & \left( {{\hat{x}}^{(m)} \neq 0} \right) \\{{\hat{h}}_{LS},} & \left( {{\hat{x}}^{(m)} = 0} \right)\end{matrix} \right.}\end{matrix} & \left( {{formula}\mspace{14mu} 76} \right)\end{matrix}$

The above formula 76 shows that when the external symbol replica isused, the channel estimation value obtained from the data signal in them-th OFDM symbol may be merely subtracted from the channel estimationvalue used in the second embodiment. Moreover, a value of β^((m)) at thetime of the channel estimation of the m-th OFDM symbol is represented bya following formula 77.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 77} \right\rbrack & \; \\{\beta^{(m)} = {\frac{K}{L}\frac{E_{p} + {{\hat{M}}^{(m)}E_{s}}}{E_{s}}}} & \left( {{formula}\mspace{14mu} 77} \right)\end{matrix}$

In this manner, by using the external symbol replica in the iterativechannel estimation, an influence by the previous channel estimation isnot accumulated in the channel estimation value in the OFDM, thus makingit possible to perform appropriate iterative processing based on turboprinciple. As a result thereof, accuracy of the iterative channelestimation is improved, thus making it possible to improve transmissionperformance. Further, since the calculation of the LLR is to beperformed based on the formula 73, calculation of an index becomesunnecessary, thus making it possible to reduce an amount of calculationsignificantly compared to the formula 53 of the second embodiment.

A program which is operated in the base station device and the terminaldevice related to each of the embodiments and modified examples thereofdescribed above is a program which controls a CPU and the like (programthat causes a computer to function) so as to realize functions of thebase station device and the terminal device in each of the embodimentsand modified examples thereof described above. In addition, informationwhich is handled by the devices is temporarily accumulated in a RAM atthe time of processing thereof, and then stored in various ROMs or anHDD, and is read, modified, and written by the CPU as necessary. Arecording medium that stores the program may be any of a semiconductormedium (for example, a ROM, a nonvolatile memory card or the like), anoptical recording medium (for example, a DVD, an MO, an MD, a CD, a BDor the like) or a magnetic recording medium (for example, a magnetictape, a flexible disc or the like). Moreover, there is a case where, byexecuting the loaded program, not only the functions of the embodimentsdescribed above are realized, but also by performing processing incooperation with an operating system, other application programs or thelike based on an instruction of the program, the functions of theinvention are realized.

When being distributed in the market, the program is able to be storedin a portable recording medium and distributed or be transferred to aserver computer connected through a network such as the Internet. Inthis case, a storage device of the server computer is also included inthe invention. A part or all of the base station device and the terminaldevice in the embodiments described above may be realized as an LSIwhich is a typical integrated circuit. Each functional block of the basestation device and the terminal device may be individually formed into achip, or a part or all thereof may be integrated and formed into a chip.Further, a method for making into an integrated circuit is not limitedto the LSI and a dedicated circuit or a versatile processor may be usedfor realization.

When each functional block is made into an integrated circuit, anintegrated circuit control unit for controlling them is added.

Further, a method for making into an integrated circuit is not limitedto the LSI and a dedicated circuit or a versatile processor may be usedfor realization. In a case where a technique for making into anintegrated circuit in place of the LSI appears with advance of asemiconductor technology, an integrated circuit by the technique may bealso used.

The invention of the present application is not limited to theembodiments described above. The terminal device of the invention of thepresent application is not limited to be applied to a mobile stationdevice, but, needless to say, is applicable to stationary or unmovableelectronic equipment which is installed indoors or outdoors such as, forexample, AV equipment, kitchen equipment, a cleaning/washing machine,air conditioning equipment, office equipment, an automatic vendingmachine, other domestic equipment, and the like.

As above, the embodiments of the invention have been described in detailwith reference to drawings, but specific configurations are not limitedto the embodiments, and a design change and the like within a scapewhich is not departed from the main subject of the invention are alsoincluded. The invention can be modified variously within the scopedefined by the claims, and embodiments obtained by appropriatelycombining technical means disclosed in different embodiments are alsoincluded in the technical scope of the invention. The configuration inwhich elements described in each of the aforementioned embodiments andachieving similar effects are replaced with each other is also included.

(1) One aspect of the invention is a reception device including: areception unit for receiving a signal representing a bit sequence; achannel estimation unit for estimating channel variation that the signalundergoes and calculating a channel estimation value representing thechannel variation; and a demodulation unit for demodulating the signalby using the channel estimation value and restoring each bit included inthe bit sequence, in which the demodulation unit performs demodulationof the signal by using a value indicating magnitude of error included inthe channel estimation value.

(2) Another aspect of the invention is the reception device according to(1), in which the demodulation unit may perform the demodulation byusing a probability density function that is a probability densityfunction of the signal and that is a product of two probability densityfunctions each represents a corresponding independent Gaussian variableby using at least the signal and the value indicating the magnitude ofthe error.

(3) Another aspect of the invention is the reception device according to(1) or (2), which may include a decoding unit for performing errorcorrection decoding for the bit restored by the demodulation unit byusing a state transition probability according to reception power of thesignal.

(4) Another aspect of the invention is the reception device according toany one of (1) to (3), which may include a decoding unit for performingerror correction decoding for the bit restored by the demodulation unit;and a replica generation unit for generating a replica of a transmissionsymbol by using the bit subjected to the error correction decoding, andin which channel estimation by the channel estimation unit, demodulationby the demodulation unit, error correction decoding by the decoding unitand generation of the replica by the replica generation unit areperformed iteratively, and the channel estimation unit performs channelestimation by using the replica generated by the replica generation insecond and subsequent times of the iteration.

(5) Another aspect of the invention is the reception device according toany one of (1) to (4), in which the channel estimation unit calculates,for each reception symbol included in the received signal, a channelestimation value used for demodulating the reception symbol, and achannel estimation value used for demodulating a first reception symbolis a value obtained by performing channel estimation without using areplica of a transmission symbol of the first reception symbol.

(6) Another aspect of the invention is a reception method, including: afirst step of receiving a signal representing a bit sequence; a secondstep of estimating channel variation that the signal undergoes andcalculating a channel estimation value representing the channelvariation; and a third step of demodulating the signal by using thechannel estimation value and restoring each bit included in the bitsequence, in which demodulation of the signal is performed by using avalue indicating magnitude of error included in the channel estimationvalue at the third step.

One aspect of the invention is applicable to, for example, a receptiondevice which needs to suppress error included in a bit LLR obtained bydemodulation using a channel estimation value.

REFERENCE SIGNS LIST

-   -   10 communication system    -   101 base station device    -   102, 102 a terminal device    -   201 coding unit    -   202 interleave unit    -   203 modulation unit    -   204 reference signal generation unit    -   205 frame composition unit    -   206 IFFT unit    -   207 CP insertion unit    -   208 radio transmission unit    -   209 transmit antenna    -   401 receive antenna    -   402 radio reception unit    -   403 CP removal unit    -   404 FFT unit    -   405 data signal extraction unit    -   406, 406 a channel estimation unit    -   407, 407 a demodulation unit    -   408 de-interleave unit    -   409, 409 a decoding unit    -   501 MSE setting unit    -   502 first variable calculation unit    -   503 absolute value acquisition unit    -   504 second variable calculation unit    -   505 absolute value acquisition unit    -   506 absolute value acquisition unit    -   507 LLR calculation unit    -   801 interleave unit    -   802 replica generation unit    -   803 replica absolute value correction unit    -   804 reference signal generation unit

What is claimed is:
 1. A reception device, comprising: a reception unitfor receiving a signal representing a bit sequence; a channel estimationunit for estimating channel variation that the signal undergoes andcalculating a channel estimation value representing the channelvariation; and a demodulation unit for demodulating the signal by usingthe channel estimation value and restoring each bit included in the bitsequence, wherein the demodulation unit performs demodulation of thesignal by using a value indicating magnitude of error included in thechannel estimation value.
 2. The reception device according to claim 1,wherein the demodulation unit performs the demodulation by using aprobability density function that is a probability density function ofthe signal and that is a product of two probability density functionseach represents a corresponding independent Gaussian variable by usingat least the signal and the value indicating the magnitude of the error.3. The reception device according to claim 1, further comprising: adecoding unit for performing error correction decoding for the bitrestored by the demodulation unit by using a state transitionprobability according to reception power of the signal.
 4. The receptiondevice according to claim 1, further comprising: a decoding unit forperforming error correction decoding for the bit restored by thedemodulation unit; and a replica generation unit for generating areplica of a transmission symbol by using the bit subjected to the errorcorrection decoding, wherein channel estimation by the channelestimation unit, demodulation by the demodulation unit, error correctiondecoding by the decoding unit and generation of the replica by thereplica generation unit are performed iteratively, and the channelestimation unit performs channel estimation by using the replicagenerated by the replica generation in second and subsequent times ofthe iteration.
 5. The reception device according to claim 1, wherein thechannel estimation unit calculates, for each reception symbol includedin the received signal, a channel estimation value used for demodulatingthe reception symbol, and a channel estimation value used fordemodulating a first reception symbol is a value obtained by performingchannel estimation without using a replica of a transmission symbol ofthe first reception symbol.
 6. A reception method, comprising: a firststep of receiving a signal representing a bit sequence; a second step ofestimating channel variation that the signal undergoes and calculating achannel estimation value representing the channel variation; and a thirdstep of demodulating the signal by using the channel estimation valueand restoring each bit included in the bit sequence, whereindemodulation of the signal is performed by using a value indicatingmagnitude of error included in the channel estimation value at the thirdstep.